Which smartphone for a smartphone-based spectrometer?

Pituła, Emil; Koba, Marcin; Śmietana, Mateusz

doi:10.1016/j.optlastec.2021.107067

Cited by 8 publications

(7 citation statements)

References 11 publications

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“…The lowest excited energy level ( 4 F9/2) of the Dy 3+ ion (478 nm) (A3) is similar to that ( 5 D4) of the Tb 3+ ion (490 nm) (B4), and dysprosium (III) complexes exhibit the characteristic 4 F9/2-6 H13/2 and 4 F9/2-6 H15/2 transitions leading to blue (around 478 nm) and the most intensive emission, yellow (around 574 nm), respectively, as shown in Figure 2a [16]. The emission spectra in sample B4 are in two luminescence bands-a weak emission at around 481 nm in blue region corresponding to the transitions 5 D4-7 F6 obeys the magnetic dipole transition selection rule of ΔJ = ±1 [17,18] and a very strong one centered at 543 nm, relevant to transition 5 D4-7 F5, in strong green region, respectively, as shown in Figure 2b.…”

Section: Excitation-emission Spectramentioning

confidence: 70%

“…These include uses in anti-counterfeiting [8,9] and potential applications in plasma displays [10]. In all of the above and in other applications, it is of crucial importance to be able to detect, identify, and track such luminescent markers remotely using worldwide available smartphones [11][12][13][14][15][16], which are more affordable than professional spectrometers and are compatible with Internet of Things technology, thus allowing intelligent sensing networks to be developed.…”

Section: Introductionmentioning

confidence: 99%

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Rare-Earth-Ion (RE3+)-Doped Aluminum and Lanthanum Borates for Mobile-Phone-Interrogated Luminescent Markers

Hristova,

Kostova,

Eftimov

et al. 2024

Photonics

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In this paper, we present the synthesis and luminescent spectra of rare-earth (RE)-doped aluminum and lanthanum borates intended to serve as narrow excitation–emission band fluorescent markers. We perform a detailed 3D excitation–emission matrix (EEM) analysis of their spectra, compare the measurements from both standard and mobile phone spectrometers, and outline the basic differences and advantages of each method. While smartphones have a different and non-uniform spectral response compared to standard spectrometers, it is shown that they offer a number of advantages such as contactless interrogation, efficient suppression of the UV excitation light, and simultaneous spectral analysis of spatially arranged arrays of fluorescent markers. The basic emission peaks have been observed and their corresponding electronic transitions identified. The obtained results show that the rare-earth-doped La and Al borates feature excitation–emission bandwidths as low 15 nm/12 nm, which makes them particularly appropriate for use as luminescent markers with UV LED excitation and smartphone interrogation.

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Section: Excitation-emission Spectramentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Rare-Earth-Ion (RE3+)-Doped Aluminum and Lanthanum Borates for Mobile-Phone-Interrogated Luminescent Markers

Hristova,

Kostova,

Eftimov

et al. 2024

Photonics

View full text Add to dashboard Cite

show abstract

“…However, it had the smallest sensor pixel size of 1.0 μm, which may have affected the image capture performance since larger pixels capture more light compared to smaller ones. 42 Although Phone 4 had a larger sensor size compared to Phone 2, Phone 2 had larger sensor pixels and thus better agreement with the other smartphones. Nonetheless, this discrepancy in Phone 4 improved after colour correction from ‘moderate’ to ‘good’ for the Green values and ‘poor’ to ‘exceptional’ for the Blue values.…”

Section: Discussionmentioning

confidence: 99%

Improving the reliability of smartphone-based urine colorimetry using a colour card calibration method

et al. 2023

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Objective Urine colorimetry using a digital image–based colorimetry is potentially an accessible hydration assessment method. This study evaluated the agreement between urine colorimetry values measured with different smartphone brands under various lighting conditions in patients with dengue fever. Methods The urine samples were photographed in a customized photo box, under five simulated lighting conditions, using five smartphones. These images were analyzed using Adobe Photoshop to obtain urine Red, Green and Blue (RGB) values with and without colour correction. A commercially available colour calibration card was used for colour correction. Using intraclass correlation coefficient (ICC), inter-phone and intra-phone agreements of urine RGB values were analyzed. Results Without colour correction, the various smartphones produced the highest agreement for Blue and Green values under the ‘daylight’ lighting condition. With colour correction, ICC values showed ‘exceptional’ inter-phone and intra-phone agreement for the Blue and Green values (ICC > 0.9). Red values showed ‘poor’ (ICC < 0.5) agreement with and without colour correction in all lighting conditions. Out of the five phones compared in this study, Phone 4 produced the lowest intra-phone agreement. Conclusions Colour calibration using photo colour cards improved the reliability of smartphone-based urine colorimetry, making this a promising point-of-care hydration assessment tool using the ubiquitous smartphone.

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“…This adaptation of diffraction gratings on the camera sensor provides the capability to separate the spectrum into individual wavelengths. Consequently, light can be effectively dissected into its spectral components based on their distinct wavelengths [55,56]. Unlike smartphone cameras, which are not specifically tailored for spectral analysis applications, placing the diffraction grating in front of a smartphone's camera sensor allows the smartphone to capture the diffraction spectrum as an image.…”

Section: Diffraction Gratingmentioning

confidence: 99%

A Citizen Science Tool Based on an Energy Autonomous Embedded System with Environmental Sensors and Hyperspectral Imaging

Kouzinopoulos,

Pechlivani,

Giakoumoglou

et al. 2024

JLPEA

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Citizen science reinforces the development of emergent tools for the surveillance, monitoring, and early detection of biological invasions, enhancing biosecurity resilience. The contribution of farmers and farm citizens is vital, as volunteers can strengthen the effectiveness and efficiency of environmental observations, improve surveillance efforts, and aid in delimiting areas affected by plant-spread diseases and pests. This study presents a robust, user-friendly, and cost-effective smart module for citizen science that incorporates a cutting-edge developed hyperspectral imaging (HI) module, integrated in a single, energy-independent device and paired with a smartphone. The proposed module can empower farmers, farming communities, and citizens to easily capture and transmit data on crop conditions, plant disease symptoms (biotic and abiotic), and pest attacks. The developed HI-based module is interconnected with a smart embedded system (SES), which allows for the capture of hyperspectral images. Simultaneously, it enables multimodal analysis using the integrated environmental sensors on the module. These data are processed at the edge using lightweight Deep Learning algorithms for the detection and identification of Tuta absoluta (Meyrick), the most important invaded alien and devastating pest of tomato. The innovative Artificial Intelligence (AI)-based module offers open interfaces to passive surveillance platforms, Decision Support Systems (DSSs), and early warning surveillance systems, establishing a seamless environment where innovation and utility converge to enhance crop health and productivity and biodiversity protection.

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Which smartphone for a smartphone-based spectrometer?

Cited by 8 publications

References 11 publications

Rare-Earth-Ion (RE3+)-Doped Aluminum and Lanthanum Borates for Mobile-Phone-Interrogated Luminescent Markers

Rare-Earth-Ion (RE3+)-Doped Aluminum and Lanthanum Borates for Mobile-Phone-Interrogated Luminescent Markers

Improving the reliability of smartphone-based urine colorimetry using a colour card calibration method

A Citizen Science Tool Based on an Energy Autonomous Embedded System with Environmental Sensors and Hyperspectral Imaging

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